Author

Haz Sameen Shahgir

University of California, RiversideORCID 0009-0008-0892-6832Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:long-read sequencing· 2 Research Focus:sequence-to-function modeling· 2 Approach:transformer / foundation model· 2 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Approach:large language model· 1 Assay:proteomics· 1

Frequent Co-Authors

Md Toki TahmidiD· 2 shared Atif Hasan RahmaniD· 1 shared Khondker Salman SayeediD· 1 shared Md. Rownok Zahan RatuliD· 1 shared Md. Shamsuzzoha BayzidiD· 1 shared Sazan MahbubiD· 1 shared Yue DongiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 12 mutual co-author links

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2 shared papersBioinformatics

Md Toki TahmidORCID

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2 papers

Recent·Most cited

BioinformaticsCommunications BiologyPeer-reviewedNov 20, 2025

BiRNA-BERT Allows Efficient RNA Language Modeling with Adaptive Tokenization

Md Toki Tahmid, Haz Sameen Shahgir, Sazan Mahbub…·Md. Shamsuzzoha Bayzid

BiRNA-BERT is a Transformer-based model pretrained on RNA sequences using adaptive tokenization, achieving state-of-the-art results in long-sequence tasks and efficient performance on short sequences.

16 citationstop 4%

long-read sequencingproteomics

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BioinformaticsbioRxivPreprintSep 23, 2024

RNA-DCGen: Dual Constrained RNA Sequence Generation with LLM-Attack

Haz Sameen Shahgir, Md. Rownok Zahan Ratul, Md Toki Tahmid…·Atif Hasan Rahman

RNA-DCGen generates RNA sequences with specific structural or functional properties using a language model, outperforming random baselines in structure prediction.

3 citations

long-read sequencingdeep learning

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